Jason White
Senior Manager, Privacy Engineering at Shopify
Greater Ottawa Metropolitan Area Canada
Summary
👤
Senior🎓
Top SchoolJason White is a senior privacy engineering leader with 11 years in data engineering and a decade-plus career building scalable analytics at Shopify, where he progressed from technical lead to Senior Manager of Privacy Engineering. He specializes in Python and Apache Spark for large-scale ETL and streaming, with deep SQL experience across Redshift, Vertica, and MySQL, and occasional work in Ruby, Scala, and C#. Jason has led cross-functional teams to replace legacy ELT systems, prepare for Shopify’s IPO, and implement near-real-time risk workflows using Spark Streaming and Kafka. He is also an active contributor to Apache Spark, improving PySpark performance and Kafka backpressure handling—work that reflects both production-grade debugging and performance optimization skills. Based in the Greater Ottawa area, he pairs engineering management and privacy-focused delivery with an M.Eng. in Engineering Management and an electrical engineering background.
12 years of coding experience
13 years of employment as a software developer
Master of Engineering (M.Eng.), Engineering Management, Master of Engineering (M.Eng.), Engineering Management at University of Ottawa / Université d'OttawaB.App.Sc., Electrical Engineering, B.App.Sc., Electrical Engineering at Queen's University
German, English
Github Skills (11)
scala10
kafka10
pyspark10
spark10
python10
streaming10
data-engineering10
testing9
sql8
javas6
java6
Programming languages (5)
Github contributions (5)
apache/spark
Oct 2015 - Nov 2017
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Back-end Developer & Data Engineer
Back-end Developer & Data EngineerContributions:7 PRs, 49 comments in 2 years 1 month
Contributions summary:Jason contributed to Apache Spark by addressing various issues related to data processing and streaming. Their work included improvements to PySpark, specifically optimizing DataFrame creation from RDDs and fixing timestamp handling. They also implemented backpressure enhancements for Kafka streaming, enabling better handling of unbalanced partitions. The user further demonstrated expertise in testing and debugging, as evidenced by the addition of new tests and the correction of existing functionalities within the Spark framework.
apache-sparkpythonscalarjava
JasonMWhite/gitlawca-scraper
May 2015 - Jun 2015
Contributions:127 commits, 90 PRs, 100 pushes in 23 days
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